Quantifying interpersonal influence in face-to-face conversations based on visual attention patterns
CHI '06 Extended Abstracts on Human Factors in Computing Systems
Using audio and video features to classify the most dominant person in a group meeting
Proceedings of the 15th international conference on Multimedia
The AMI meeting corpus: a pre-announcement
MLMI'05 Proceedings of the Second international conference on Machine Learning for Multimodal Interaction
Dominance detection in meetings using easily obtainable features
MLMI'05 Proceedings of the Second international conference on Machine Learning for Multimodal Interaction
ICMI '08 Proceedings of the 10th international conference on Multimodal interfaces
Automatic nonverbal analysis of social interaction in small groups: A review
Image and Vision Computing
IEEE Transactions on Multimedia
Multimodal support for social dynamics in co-located meetings
Personal and Ubiquitous Computing
Hi-index | 0.00 |
This paper addresses the problem of automatically predicting the dominant clique (i.e., the set of K-dominant people) in face-to-face small group meetings recorded by multiple audio and video sensors. For this goal, we present a framework that integrates automatically extracted nonverbal cues and dominance prediction models. Easily computable audio and visual activity cues are automatically extracted from cameras and microphones. Such nonverbal cues, correlated to human display and perception of dominance, are well documented in the social psychology literature. The effectiveness of the cues were systematically investigated as single cues as well as in unimodal and multimodal combinations using unsupervised and supervised learning approaches for dominant clique estimation. Our framework was evaluated on a five-hour public corpus of teamwork meetings with third-party manual annotation of perceived dominance. Our best approaches can exactly predict the dominant clique with 80.8% accuracy in four-person meetings in which multiple human annotators agree on their judgments of perceived dominance.